Methods and systems for distributed coordination

ABSTRACT

At least one example embodiment discloses a method of scheduling communications in a network having a plurality of base stations covering cells, respectively. The method includes obtaining a first coordination matrix, by a first base station, based on channel state information from at least one user equipment (UE), the first coordination matrix indicating scheduling information and first weights associated with subband transmissions for the first base station, transmitting the first coordination matrix to at least another base station of the plurality of base stations, receiving, by the first base station, a second coordination matrix from the at least another base station, the second coordination matrix indicating second weights associated with subband transmissions for the second base station, and transmitting, by the first base station, in subbands where the associated first weights are greater than the associated second weights.

CROSS-REFERENCE TO RELATED APPLICATIONS

This non-provisional patent application claims priority under 35 U.S.C.§119(e) to provisional U.S. application No. 61/883,545 filed on Sep. 27,2013 in the United States Patent and Trademark Office, the entirecontents of which are incorporated herein by reference.

BACKGROUND

Wireless networks using the long-term evolution (LTE) standard mayemploy features, such as Carrier Aggregation (CA) and CoordinatedMulti-Point Operation (CoMP), that allow UEs to be serviced by more thanone base station. For example, when a UE works under the CA mode, the UEmay be served by two or more cells, where one of the cells acts as aprimary serving cell, and other cells act as secondary serving cells.Similarly, CoMP allows UEs to be served by more than one base station inorder to enhance quality of service (QoS) on the perimeter of a servingcell.

Resource and spatial coordination are aspects of CoMP technologies inwireless communications to improve system capacity. Most of techniquesin the CoMP technology developments use a centralizedcontroller/scheduler for resource and spatial coordination amongtransmission points (TPs) in the CoMP cooperating set.

SUMMARY

The inventors have discovered methods for distributed coordination witha non-centralized scheduler.

At least one example embodiment discloses a method of distributedresource and spatial coordination with non-centralized schedulers. Eachscheduler in a base station is in charge of its scheduling decision andtakes into account schedules distributed from other schedulers in otherbase stations.

At least one example embodiment discloses a method of schedulingcommunications in a network having a plurality of base stations coveringcells, respectively. The method includes obtaining a first coordinationmatrix, by a first base station, based on channel state information fromat least one user equipment (UE), the first coordination matrixindicating scheduling information and first weights associated withsubband transmissions for the first base station, transmitting the firstcoordination matrix to at least another base station of the plurality ofbase stations, receiving, by the first base station, a secondcoordination matrix from the at least another base station, the secondcoordination matrix indicating second weights associated with subbandtransmissions for the second base station, and transmitting, by thefirst base station, in subbands where the associated first weights aregreater than the associated second weights.

In an example embodiment, the method includes determining the firstweights based on feedback from the at least one UE, the feedbackincluding at least one of precoding matrix indicator (PMI), channelquality indicator (CQI) and rank indicator (RI) feedback.

In an example embodiment, the determining the first weights is furtherbased on at least one of buffer status, network load, user priority,traffic priority and cost index.

In an example embodiment, the determining the first weights includesreceiving a weighting function from operations, administration andmanagement (OAM), the first weights being based on the weightingfunction.

In an example embodiment, the weighting function allocates priority tothe plurality of base stations.

In an example embodiment, the first coordination matrix indicates firstprecoding matrix indicators associated with the first base station andundesirable precoding matrix indicators associated with the at leastanother base station.

In an example embodiment, the second coordination matrix indicatessecond precoding matrix indicators.

In an example embodiment, the method further includes adjusting thescheduling information in subbands where one of the second precodingmatrix indicators matches one of the undesirable precoding matrixindicators.

In an example embodiment, the first coordination matrix indicates atleast one of first UE IDs associated with the first base station andundesirable UE IDs associated with the at least another base station.

In an example embodiment, the second coordination matrix indicatessecond UE IDs.

In an example embodiment, the method further includes adjusting thescheduling information in subbands where one of the second UE IDsmatches one of the undesirable UE IDs where the associated first weightsare less than the associated second weights.

In an example embodiment, the first coordination matrix indicates atleast one of first transmit power levels associated with the first basestation and undesirable transmit power levels associated with the atleast another base station.

In an example embodiment, the second coordination matrix indicatessecond transmit power levels.

In an example embodiment, the method further includes adjusting thescheduling information where the associated first weights are less thanthe associated second weights, the scheduling information indicatingtransmission power levels for the subbands where the associated firstweights are less than the associated second weights.

In an example embodiment, the first coordination matrix indicates firstprecoding matrix indicators associated with the first base station anddesirable precoding matrix indicators associated with the at leastanother base station.

In an example embodiment, the first coordination matrix indicates firstUE IDs associated with the first base station and desirable UE IDsassociated with the at least another base station.

In an example embodiment, the first coordination matrix indicates firsttransmission power levels associated with the first base station anddesirable transmission power levels associated with the at least anotherbase station.

In an example embodiment, the method further includes adjusting thescheduling information in subbands where the associated first weightsare less than the associated second weights.

In an example embodiment, the first coordination matrix is based oninformation not directly from other base stations.

At least one example embodiment discloses a base station including amemory and a processor configured to obtain a first coordination matrixbased on channel state information from at least one user equipment(UE), the first coordination matrix indicating scheduling informationand first weights associated with subband transmissions for the basestation, a transmitter configured to transmit the first coordinationmatrix to at least another base station of the plurality of basestations, and a receiver configured to receive a second coordinationmatrix from the at least another base station, the second coordinationmatrix indicating second weights associated with subband transmissionsfor the second base station, and the transmitter being furtherconfigured to transmit in subbands where the associated first weightsare greater than the associated second weights.

In an example embodiment, the processor is configured to determine thefirst weights based on feedback from the at least one UE, the feedbackincluding at least one of precoding matrix indicator (PMI), channelquality indicator (CQI) and rank indicator (RI) feedback.

In an example embodiment, the processor is configured to determinefurther based on at least one of buffer status, network load, userpriority, traffic priority and cost index.

In an example embodiment, the processor is configured to determine thefirst weights based on a weighting function from OAM, the first weightsbeing based on the weighting function.

In an example embodiment, the weighting function allocates priority tothe plurality of base stations.

In an example embodiment, the first coordination matrix indicates firstprecoding matrix indicators associated with the first base station andundesirable precoding matrix indicators associated with the at leastanother base station.

In an example embodiment, the second coordination matrix indicatessecond precoding matrix indicators.

In an example embodiment, the processor is configured to adjust thescheduling information where the associated first weights are less thanthe associated second weights, the scheduling information indicatingtransmission power levels for the subbands where the associated firstweights are less than the associated second weights.

In an example embodiment, the first coordination matrix indicates atleast one of a first UE IDs associated with the first base station andundesirable UE IDs associated with the at least another base station.

In an example embodiment, the second coordination matrix indicatessecond UE IDs.

In an example embodiment, the processor is configured to adjust thescheduling information in subbands where one of the second UE IDsmatches one of the undesirable UE IDs where the associated first weightsare less than the associated second weights.

In an example embodiment, the first coordination matrix indicates atleast one of first transmit power levels associated with the first basestation and undesirable transmit power levels associated with the atleast another base station.

In an example embodiment, the second coordination matrix indicatessecond transmit power levels.

In an example embodiment, the processor is configured to adjust thescheduling information for transmission power levels of subbands wherethe associated first weights are less than the associated secondweights.

In an example embodiment, the first coordination matrix indicates firstprecoding matrix indicators associated with the first base station anddesirable precoding matrix indicators associated with the at leastanother base station.

In an example embodiment, the first coordination matrix indicates firstUE IDs associated with the first base station and desirable UE IDsassociated with the at least another base station.

In an example embodiment, the first coordination matrix indicates firsttransmission power levels associated with the first base station anddesirable transmission power levels associated with the at least anotherbase station.

In an example embodiment, the processor is configured to adjust thescheduling information in subbands where the associated first weightsare less than the associated second weights.

In an example embodiment, the first coordination matrix is based oninformation not directly from other base stations.

BRIEF DESCRIPTION OF THE DRAWINGS

Example embodiments will be more clearly understood from the followingdetailed description taken in conjunction with the accompanyingdrawings. FIGS. 1-3 represent non-limiting, example embodiments asdescribed herein.

FIG. 1 illustrates a wireless communication system according to anexample embodiment;

FIG. 2 illustrates a method of scheduling communications in a networkhaving a plurality of base stations covering cells, respectively,according to an example embodiment; and

FIG. 3 illustrates an example embodiment of a base station shown in FIG.1.

DETAILED DESCRIPTION

Various example embodiments will now be described more fully withreference to the accompanying drawings in which some example embodimentsare illustrated.

Accordingly, while example embodiments are capable of variousmodifications and alternative forms, embodiments thereof are shown byway of example in the drawings and will herein be described in detail.It should be understood, however, that there is no intent to limitexample embodiments to the particular forms disclosed, but on thecontrary, example embodiments are to cover all modifications,equivalents, and alternatives falling within the scope of the claims.Like numbers refer to like elements throughout the description of thefigures.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. For example, a first element could be termed asecond element, and, similarly, a second element could be termed a firstelement, without departing from the scope of example embodiments. Asused herein, the term “and/or” includes any and all combinations of oneor more of the associated listed items.

It will be understood that when an element is referred to as being“connected” or “coupled” to another element, it can be directlyconnected or coupled to the other element or intervening elements may bepresent. In contrast, when an element is referred to as being “directlyconnected” or “directly coupled” to another element, there are nointervening elements present. Other words used to describe therelationship between elements should be interpreted in a like fashion(e.g., “between” versus “directly between,” “adjacent” versus “directlyadjacent,” etc.).

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of exampleembodiments. As used herein, the singular forms “a,” “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“comprises,” “comprising,” “includes” and/or “including,” when usedherein, specify the presence of stated features, integers, steps,operations, elements and/or components, but do not preclude the presenceor addition of one or more other features, integers, steps, operations,elements, components and/or groups thereof.

It should also be noted that in some alternative implementations, thefunctions/acts noted may occur out of the order noted in the figures.For example, two figures shown in succession may in fact be executedsubstantially concurrently or may sometimes be executed in the reverseorder, depending upon the functionality/acts involved.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which example embodiments belong. Itwill be further understood that terms, e.g., those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

Portions of example embodiments and corresponding detailed descriptionare presented in terms of software, or algorithms and symbolicrepresentations of operation on data bits within a computer memory.These descriptions and representations are the ones by which those ofordinary skill in the art effectively convey the substance of their workto others of ordinary skill in the art. An algorithm, as the term isused here, and as it is used generally, is conceived to be aself-consistent sequence of steps leading to a desired result. The stepsare those requiring physical manipulations of physical quantities.Usually, though not necessarily, these quantities take the form ofoptical, electrical, or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

In the following description, illustrative embodiments will be describedwith reference to acts and symbolic representations of operations (e.g.,in the form of flowcharts) that may be implemented as program modules orfunctional processes including routines, programs, objects, components,data structures, etc., that perform particular tasks or implementparticular abstract data types and may be implemented using existinghardware at existing network elements or control nodes. Such existinghardware may include one or more Central Processing Units (CPUs),digital signal processors (DSPs),application-specific-integrated-circuits, field programmable gate arrays(FPGAs) computers or the like.

Unless specifically stated otherwise, or as is apparent from thediscussion, terms such as “processing” or “computing” or “calculating”or “determining” or “displaying” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that manipulates and transforms data represented as physical, electronicquantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

As disclosed herein, the term “storage medium”, “storage unit” or“computer readable storage medium” may represent one or more devices forstoring data, including read only memory (ROM), random access memory(RAM), magnetic RAM, core memory, magnetic disk storage mediums, opticalstorage mediums, flash memory devices and/or other tangible machinereadable mediums for storing information. The term “computer-readablemedium” may include, but is not limited to, portable or fixed storagedevices, optical storage devices, and various other mediums capable ofstoring, containing or carrying instruction(s) and/or data.

Furthermore, example embodiments may be implemented by hardware,software, firmware, middleware, microcode, hardware descriptionlanguages, or any combination thereof. When implemented in software,firmware, middleware or microcode, the program code or code segments toperform the necessary tasks may be stored in a machine or computerreadable medium such as a computer readable storage medium. Whenimplemented in software, a processor or processors will perform thenecessary tasks.

A code segment may represent a procedure, function, subprogram, program,routine, subroutine, module, software package, class, or any combinationof instructions, data structures or program statements. A code segmentmay be coupled to another code segment or a hardware circuit by passingand/or receiving information, data, arguments, parameters or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

As used herein, the term “user equipment” or “UE” may be synonymous to auser equipment, mobile station, mobile user, access terminal, mobileterminal, user, subscriber, wireless terminal, terminal and/or remotestation and may describe a remote user of wireless resources in awireless communication network. Accordingly, a UE may be a wirelessphone, wireless equipped laptop, wireless equipped appliance, etc.

The term “base station” may be understood as a one or more cell sites,base stations, nodeBs, enhanced NodeBs, access points, and/or anyterminus of radio frequency communication. Although current networkarchitectures may consider a distinction between mobile/user devices andaccess points/cell sites, the example embodiments described hereaftermay also generally be applicable to architectures where that distinctionis not so clear, such as ad hoc and/or mesh network architectures, forexample.

Communication from the base station to the UE is typically calleddownlink or forward link communication. Communication from the UE to thebase station is typically called uplink or reverse link communication.

Serving base station may refer to the base station currently handlingcommunication needs of the UE.

FIG. 1 illustrates a system according to an example embodiment. Awireless communications system 100 may follow, for example, a Long TermEvolution (LTE) protocol. It should be understood that exampleembodiments are not limited to LTE.

Wireless communications system 100 includes a first eNB 110A; a secondeNB 110B; a third eNB 110C; a plurality of user equipments (UEs) 120including first UE 122; second UE 124; third UE 126; and fourth UE 128;a Gateway/MME 130. Each eNB 110A-110C may have a coverage area which maybe a single cell or a plurality of cells.

The gateway/MME 130 may include one or more processors and an associatedmemory operating together to achieve their respective functionality. Thegateway/MME 130 may include one or more mobility management entities(MME), a Home eNB Gateway, a security gateway and/or one or moreoperations, administration and management (OAM) nodes (not shown). Forthe convenience of illustration, the gateway/MME 130 is illustrated as asingle node, however, it should be understood that the gateway/MME 130may be represented as separate nodes.

It should be noted that the wireless communications system 100 is notlimited to the features shown therein. These features are shown forexplanation of example embodiments. It should be understood that thewireless communications system 100 may include common LTE features suchas a home subscriber server (HSS), an Off-line charging System (OFCS), aserving gateway (S-GW), and a public data network (PDN) gateway (P-GW).

The UEs 120 may be in wireless communication with at least a respectiveone of the first eNB 110A, the second eNB 110B and the third eNB 110C.The UEs 120 may be, for example, mobile phones, smart phones, computers,or personal digital assistants (PDAs). The first eNB 110A, the secondeNB 110B and the third eNB 110C communicate with each other over X2interfaces. More specifically, the first eNB 110A and the second eNB110B communicate over an X2 interface X_(AB), the third eNB 110C and thesecond eNB 110B communicate over an X2 interface X_(BC) and the firsteNB 110A and the third eNB 110C communicate over an X2 interface X_(AC).

The X2 interface is defined by 3GPP standards. Therefore, for the sakeof brevity, the X2 interfaces X_(AB), X_(BC) and X_(AC) will not bedescribed in greater detail.

The gateway/MME 130 communicates with the first eNB 110A, the second eNB110B and the third eNB 110C over S1 interfaces S1_(A), S1_(B) andS1_(C), respectively.

The eNBs 110A-110C are configured to perform distributed coordination.

Each base station (e.g., eNBs 110A-110C) performs a scheduling decisionindependently with a coordination policy as a constraint. Each basestation performs a provisional scheduling algorithm, such asproportionally fair, maximum C/I (carrier-to-interference) algorithm,without the constraint using known algorithms The scheduling decisions,such as resource allocation, precoding vectors of a serving eNB, andcompanion precoding matrix indicator (PMI) from neighboring eNBs in thecooperating set, are exchanged between adjacent eNBs. Each eNB isprovisioned with the coordination policy through an OAM interface by anoperator.

Each eNB 110A-110C re-computes the scheduling algorithm based on thecoordination policy and scheduling decisions from neighboring cells toachieve the common target of resource and spatial coordination.

The coordination policy defines a control function of each eNB forresource and spatial coordination and a weighting function Wi_(i,j,c) ateach eNB in a CoMP cooperating set to be incorporated into thecomputation of a scheduling matrix, where i is a subframe index, j is asubband index and c is the cell. A cooperating set is defined when theUE reports the signal strengths of neighboring cell(s) are above theconfigured threshold. Using FIG. 1 as an example, the eNBs 110A-110C maybe considered a cooperating set.

As should be understood, a subband is a portion of an operating systembandwidth within which frames containing information bits, arranged asper a particular format, are conveyed. A subframe is a portion of aframe. A combination of a sub-frame and a subband is a set of resourceblock pairs.

The weighting function W_(i,j,c) with other scheduling decisions, suchas resource allocation and precoding matrix, are specified in aninformation element to be exchanged between eNBs in the cooperating set.The control function will enforce each eNB in the CoMP cooperating setto follow the coordination policy provisioned in advance. The controlfunction is a set of rules for all eNBs in the cluster for coordinationamong schedulers. For example, the control function may follow a roundrobin rule where a rank is generated among eNBs in the cluster. Ahighest rank eNB would allocate resources first, then the second highestranked eNB and so until the last eNB with the lowest rank for a givensubframe. At a next subframe, the first eNB would move to the bottom ofrank and all other eNBs move up 1 rank. The coordination policy may bethe same for each eNB in a CoMP cluster, e.g., aligned by OAM, otherwisethe interpretation of weighting may be diverse among the eNBs. Thecontrol and weighting functions W_(i,j,c) could be time variantfunctions of variables, such as traffic arrivals and system load.

Distributed coordination for CoMP coordinating scheduling/beamformingare based on the coordinating policy and initial preliminary schedulingdecision from each eNB in the cooperating set. The control functiondefines the rule for each eNB to follow after receiving a schedulingmatrix and channel state information from each eNB 110A-110C in thecooperating set.

In distributed coordination, each eNB 110A-110C incorporates the initialscheduling matrices, UE feedbacks (such as CQI/PMI/RI and companionPMIs) and weighting functions W_(i,j,c) from neighboring cells in thecooperating set to the scheduler algorithm as the constraint forscheduling.

The eNBs 110A-110C use the weighting function W_(i,j,c) to decide thepriority of the scheduling matrix at each scheduling instance whenmultiple scheduling matrices from the CoMP cooperating set are received.The weighting function W_(i,j,c) in the distributed coordination is usedby each eNB 110A-110C to determine who has higher priority in thescheduling decision for resource and spatial coordination. The eNB withthe highest weight for the scheduled subband in the cooperating setretains its resource allocation and the preference of precoding vector.

The eNBs with a lower weighting adjust the scheduling matrix adjustingthe resource allocation, precoding vector, and/or transmitted power, tominimize the interference to the eNBs with a higher weight

The weighting function W_(i,j,c) is a function of achievable ratewithout resource or spatial coordination.

${W_{i,j,c} = {f\left( {R_{i,j,c},\Delta_{c}} \right)}},{{where}\left( \begin{matrix}{i = {{subframe}\mspace{14mu}{index}}} \\{j = {{subband}\mspace{14mu}{index}}} \\{c = {{cell}\mspace{14mu}{index}}}\end{matrix} \right.}$

The achievable rate, R_(i,j,c) is derived from a UE's CQI/PMI/RI(channel quality indicator/pre-coding matrix indicator/rank indicator)feedbacks with a given transmission power and interference. The deltafunction, Δc, is an additional function for the robust traffic arrivaland different type of users, such as Buffer Status (B), system load (L),user priority (U), traffic priority (T), and cost index (q.Δ=g(B,L,U,T,C).

The achievable rate, weighting function, and delta function are derivedby a scheduler at each eNB.

The delta function Δc may be a time variant function based on thetraffic arrival and system load. The delta function Δc may be a stepincreasing function to get higher priority in resource and spatialcoordination when the cell load is over a threshold configured byoperator. The delta function Δc could also be defined as extra bonusweight for preferred users.

The weighting function W_(i,j,c) may be specified by vendor or operatorby OAM. Such a weighting function W_(i,j,c) can be specified with acell-specific manner if necessary in order to prioritize orde-prioritize certain cells for better coverage or UE experience.Different types of weighting functions W_(i,j,c) can be provided by OAMto facilitate different prioritization strategies, e.g. PF-typeweighting function, upperbound-limited weighting function, etc.

Procedures of distributed coordination for CS/CB (coordinatedscheduling/coordinated beamforming) are described below. The examplegiven below is for facilitating beam coordination. However, exampleembodiments can be easily extended to do other types of coordination byreplacing PMI information with others, e.g. with transmission power orestimated PL from each cell which becomes CoMP semi-static/dynamic pointmuting, or with Cell IDs from each cell where some UEs become moredesirable or undesirable to be allocated in given physical resourceblocks (PRBs). Other schemes may be implemented by sharing/exchanging acombination of information, or multiple coordination matrices where eachmatrix is dedicated for one type of information sharing and individualweighting value. The type of information sharing can be pre-configuredin OAM.

Each eNB 110A-110 c performs an initial scheduling decision based onUEs' CSI (channel state information) feedbacks without resource andspatial coordination and the associated weighting function W_(i,j,c).Then, each eNB sends the coordination matrix, such as schedulingdecisions, PMIs, and weighting vectors, to the neighboring cells in theCoMP cooperating set

The coordination matrix contains subband scheduling information(sb_(i,c)), PMIs of the serving cell and neighboring cells (PMI_(i,c))and a weighting vector (W_(i,c)). An example of a coordination matrix ofeNB 110A (cell 1) is shown below.

$\begin{matrix}\; & {sb}_{1,1} & {PMI}_{1,1} & {PMI}_{1,2} & 0 & W_{1,1} \\\; & {sb}_{2,1} & {PMI}_{2,1} & 0 & 0 & W_{2,1} \\{{Cell}\mspace{14mu} 1} & {sb}_{3,1} & {PMI}_{3,1} & {PMI}_{3,2} & {PMI}_{3,3} & W_{3,1} \\\; & \; & \vdots & \; & \; & \; \\\; & {sb}_{N,1} & {PMI}_{N,1} & 0 & {PMI}_{N,3} & W_{N,1}\end{matrix}$

Since a CoMP cooperating set is a UE-specific configuration, each eNBwill send scheduling decisions to all neighboring eNBs. Each subbandscheduling decision contains resource blocks and the serving cell PMIand worst companion PMIs from the associated neighboring cells. If anyUE is configured with multiple CSI processes for CoMP coordination, allPMIs of non-serving cells are included in the coordination matrix.

PMI_(1,1) PMI_(2,1), PMI_(N,1) refer to serving cell PMIs. If a PMIequals zero, the corresponding subband and cell is free to be used byall neighboring eNBs. PMI_(1,2), PMI_(3,2), PMI_(3,3), PMI_(N,3) arePMIs (the worst companion PMI for CS/CB or best companion PMI for DPS(dynamic point selection) and JT (joint transmission)) that neighboringcells should take into consideration. Note that they can be the bestcompanion PMI if the type of information sharing is pre-configured inOAM. If it equals to zero, the corresponding subband has no spatialrestriction for the specific neighboring cell. It should be understoodthat PMI_(i,c) may contain a single PMI index or multiple indices, orsingle set index for multiple PMIs, in the event that there may be morethan one worst/best companion PMIs.

Each eNB 110A-110C re-computes their scheduling matrix based on theweighting vector after the coordination matrices from neighboring cellsare received. The scheduling matrix is a set of parameters for thescheduler to incorporate for the scheduling decision.

If the weighting vector is higher than neighboring weighting vectors,the serving cell has the highest priority and will keep its resource andprecoding vector of the subband. The neighboring eNBs will adjust thescheduling to reduce the interference after the neighboring eNBs havereceived the serving eNB's scheduling matrix. If the serving eNBdetermines that one neighboring eNB in the CoMP cooperating set in thegiven subband has a higher weighting vector than that of the servingeNB, the serving eNB adjusts the scheduling decision if the scheduledPMI is the worst companion PMI of the neighboring eNB, for example,PMI_(1,2), PMI_(3,2) or PMI_(3,3). The serving eNB may allocate theresource to another UE in a ranking list of the subband with a preferredPMI, as shown in the coordination matrix above. Additionally, theserving eNB may move the resource allocation of the UE to anothersubband.

The serving eNB is configured to determine if two neighboring eNBs inthe CoMP cooperating set in a given subband have higher weightingvectors than that of the serving eNB. The serving eNB adjusts thescheduling decision if the corresponding PMI of the serving eNB is theworst companion PMI of either one of the neighboring eNBs. Worstcompanion PMI is the PMI from a neighboring cell to create the mostinterference to the specific UE. If the PMI is not the worst companion,the interference will not be the worst for the given UE.

When the corresponding PMI of the serving eNB is the worst companion PMIof either one of the neighboring eNBs, the serving eNB allocates theresource to another UE in the ranking list of the subband with apreferred PMI. The serving eNB may move the resource allocation of theUE to another subband and repeat the process for all subbands.

FIG. 2 illustrates a method of scheduling communications in a networkhaving a plurality of base stations covering cells, respectively. Themethod of FIG. 2 may be performed by any of the eNBs 110A-110C, asdescribed above.

At S205, the eNB obtains a first coordination matrix based on channelstate information from at least one user equipment (UE), the firstcoordination matrix indicating scheduling information and first weightsassociated with subband transmissions for the base station. At S210, theeNB transmits the first coordination matrix to at least another basestation of the plurality of base stations. At S215, the eNB receives asecond coordination matrix from the at least another base station, thesecond coordination matrix indicating second weights associated withsubband transmissions for the second base station. At S220, the eNBtransmits data in subbands where the associated first weights aregreater than the associated second weights.

FIG. 3 illustrates an example embodiment of the macro eNB 110A. Itshould be also understood that the macro eNB 110A may include featuresnot shown in FIG. 3 and should not be limited to those features that areshown.

Referring to FIG. 3, the base station 110A may include, for example, adata bus 259, a transmitting unit 252, a receiving unit 254, a memoryunit 256, and a processing unit 258.

The transmitting unit 252, receiving unit 254, memory unit 256, andprocessing unit 258 may send data to and/or receive data from oneanother using the data bus 259. The transmitting unit 252 is a devicethat includes hardware and any necessary software for transmittingwireless signals including, for example, data signals, control signals,and signal strength/quality information via one or more wirelessconnections to other network elements in the wireless communicationsnetwork 100.

The receiving unit 254 is a device that includes hardware and anynecessary software for receiving wireless signals including, forexample, data signals, control signals, and signal strength/qualityinformation via one or more wireless connections to other networkelements in the network 100.

The memory unit 256 may be any device capable of storing data includingmagnetic storage, flash storage, etc. The memory unit 256 is used fordata and controlling signal buffering and storing for supportingpre-scheduling and the scheduled data transmissions andre-transmissions.

The processing unit 258 may be any device capable of processing dataincluding, for example, a microprocessor configured to carry outspecific operations based on input data, or capable of executinginstructions included in computer readable code. The processing unit 258may include a scheduler.

For example, the processing unit 258 is capable of obtaining a firstcoordination matrix, by a first base station, based on channel stateinformation from at least one user equipment (UE), the firstcoordination matrix indicating scheduling information and first weightsassociated with subband transmissions for the first base station.Furthermore, the processing unit 258 is configured to adjust thescheduling of the macro eNB 110A.

Example embodiments being thus described, it will be obvious that thesame may be varied in many ways. Such variations are not to be regardedas a departure from the spirit and scope of example embodiments, and allsuch modifications as would be obvious to one skilled in the art areintended to be included within the scope of the claims.

What is claimed is:
 1. A method of scheduling communications in anetwork having a plurality of base stations covering cells,respectively, the method comprising: determining first weights based onfeedback from at least one user equipment (UE), the feedback includingat least one of precoding matrix indicator (PMI), channel qualityindicator (COI) and rank indicator (RI) feedback, the determiningincluding, receiving a weighting function configured by an operations,administration and management (OAM) function, the first weights beingbased on the weighting function, the weighting function being associatedwith at least one subframe, at least one subband and at least one of thecells; obtaining a first coordination matrix, by a first base station,based on channel state information from the at least one, the firstcoordination matrix indicating scheduling information and first weightsassociated with subband transmissions for the first base station;transmitting, by the first base station, the first coordination matrixto at least another base station of the plurality of base stations;receiving, by the first base station, a second coordination matrix fromthe at least another base station, the second coordination matrixindicating second weights associated with subband transmissions for theat least another base station; and transmitting, by the first basestation, data in subbands where the associated first weights are greaterthan the associated second weights.
 2. The method of claim 1, whereinthe step of determining the first weights is further based on at leastone of buffer status, network load, user priority, traffic priority andcost index.
 3. The method of claim 1, wherein the plurality of basestations are in a cooperating set and the weighting function allocatespriority to the plurality of base stations within the cooperating set.4. The method of claim 1, wherein the first coordination matrixindicates first precoding matrix indicators associated with the firstbase station and undesirable precoding matrix indicators associated withthe at least another base station.
 5. The method of claim 4, wherein thesecond coordination matrix indicates second precoding matrix indicators.6. The method of claim 5, further comprising: adjusting the schedulinginformation in subbands where one of the second precoding matrixindicators matches one of the undesirable precoding matrix indicatorswhere the associated first weights are less than the associated secondweights.
 7. The method of claim 1, wherein the first coordination matrixindicates at least one of first UE IDs associated with the first basestation and undesirable UE IDs associated with the at least another basestation.
 8. The method of claim 7, wherein the second coordinationmatrix indicates second UE IDs.
 9. The method of claim 8, furthercomprising: adjusting the scheduling information in subbands where oneof the second UE IDs matches one of the undesirable UE IDs where theassociated first weights are less than the associated second weights.10. The method of claim 1, wherein the first coordination matrixindicates at least one of first transmit power levels associated withthe first base station and undesirable transmit power levels associatedwith the at least another base station.
 11. The method of claim 10,wherein the second coordination matrix indicates second transmit powerlevels.
 12. The method of claim 11, further comprising: adjusting thescheduling information where the associated first weights are less thanthe associated second weights, the scheduling information indicatingtransmission power levels for the subbands where the associated firstweights are less than the associated second weights.
 13. The method ofclaim 1, wherein the first coordination matrix indicates first precodingmatrix indicators associated with the first base station and desirableprecoding matrix indicators associated with the at least another basestation.
 14. The method of claim 1, wherein the first coordinationmatrix indicates first UE IDs associated with the first base station anddesirable UE IDs associated with the at least another base station. 15.The method of claim 1, wherein the first coordination matrix indicatesfirst transmission power levels associated with the first base stationand desirable transmission power levels associated with the at leastanother base station.
 16. The method of claim 1, further comprising:adjusting the scheduling information in subbands where the associatedfirst weights are less than the associated second weights.
 17. Themethod of claim 1, wherein the first coordination matrix is based oninformation not directly from other base stations.
 18. The method ofclaim 1, wherein the weighting function is a function of achievable ratewithout resource or spatial coordination.
 19. The method of claim 18,wherein the weighting function is also a function of a step functionthat increases in accordance with a priority of the first base station.20. A base station in a network, the base station comprising: aprocessor configured to, determine first weights based on feedback fromat least one user equipment (UE), the feedback including at least one ofprecoding matrix indicator (PMI), channel quality indicator (COI) andrank indicator (RI) feedback, the determining including, receive aweighting function configured by an operations, administration andmanagement (OAM) function, the first weights being based on theweighting function, the weighting function being associated with atleast one subframe, at least one subband and at least one of the cells,obtain a first coordination matrix based on channel state informationfrom the at least one, the first coordination matrix indicatingscheduling information and first weights associated with subbandtransmissions for the base station, transmit the first coordinationmatrix to at least another base station of a plurality of other basestations in the network, receive a second coordination matrix from theat least another base station, the second coordination matrix indicatingsecond weights associated with subband transmissions for the at leastanother base station, and transmit data in subbands where the associatedfirst weights are greater than the associated second weights.